Lars Kai Hansen

Can artificial intelligence algorithms learn to communicate in a language we understand?

Lars Kai Hansen says: “Machine learning algorithms are often perceived as complex black boxes and much research has already gone into opening the black box to explain what has been learned from data. The communication aspects of explainable AI have attracted less attention. The cognitive spaces project is aimed at relating AI explanations better to given user groups and effectively let the algorithms speak the user’s language. We will realize the vision by aligning learned representations of data with formal human knowledge graphs. We hope to understand and push the limits to deep learning interactivity by theoretical and experimental analysis, design of new learning schemes to enable knowledge aware models and explanation.

Our primary use case concerns cognitive spaces for deeper understanding of electric brainwaves (EEG). These signals are of increasing diagnostic importance and EEG signals play a fundamental role in neuroscience. In an ambitious attempt to understand EEG models better we will use cognitive space methods for real-time “captioning” of the brainwave signal”.

Since 2000 Lars Kai Hansen has been a Professor at Technical University of Denmark where he heads the Cognitive Systems group.

Kjeld Schmiegelow

Kjeld Schmiegelow says: “We know of more than 6,000, most often hereditary, “rare diseases” (RD), including childhood cancer. Together, the RD affects more than 250 million people worldwide. In children, cancer is responsible for 20% of all deaths. In PREDICT, we will use cancer in children, and especially leukemia (most common childhood cancer), as a prototype for RD and provide new knowledge about what variations in human genetic material mean for the development of cancer (and other diseases) and for the course of the disease. Using modern genetic engineering, including a new method of analysis that we have developed, we will (i) identify individuals who have a congenital increased risk of developing cancer, (ii) identify whether the new method of analysis can be used in the national screening of newborns for hereditary diseases, (iii) examine thousands of cancer patients to map the effects of hereditary factors on cure rates and the incidence of side effects, and (iv) uncover how patients and healthy individuals experience the application of the new knowledge about their genes.”

Kjeld Schmiegelow is Consultant at the Juliane Marie Centre, Rigshospitalet, and professor in Pediatrics at Department of Clinical Medicine, Copenhagen University since 2005.

Henning Bundgaard

Henning Bundgaard says: “Certain environmental factors and disorders in the expecting mother are associated with heart defects in the newborn. However, these factors may also be associated with more subtle abnormalities in the newborn heart that may present much later in life. This project will investigate the association between common maternal risk factors (diabetes, thyroid and connective tissue disorders) and more overt modifiable factors (smoking, weight and night-shifts) during pregnancy and the impact on the heart in the newborn and later in childhood, through heart examinations of children at birth and again at 5 and 10 years of age. This project will generate knowledge of which neonatally identified subtle abnormalities may require follow-up or even early intervention. The major expectation is to obtain insight into the effects or contributing factors to subgroups of cardiac disorders seen in adults including coronary artery disease, arrhythmias, heart failure, valve calcification and hypertension.”

Henning Bundgaard is Consultant in cardiology at Department of Cardiology, Rigshospitalet, and has been Professor at Institute for Clinical Medicine, University of Copenhagen, since 2015.

Photo: Rigshospitalet

Eva Hoffmann

Eva Hoffmann says: “Up to one in 20 children are born with congenital disorders that originated in the parents’ sperm or egg. This is much higher than in other organisms and we have long wanted to understand what happens when parents pass on their DNA to their children. Questions such as what makes us different from our parents, how does our DNA change, and what can go wrong. We are now in a position to start addressing these fundamental questions about human genetics. We will generate an atlas of sequences from human eggs, sperm and embryos from earliest stages of development to explore what genetic changes we see and how these processes occur. Some of the processes lead to severe genetic aberrations that result in infertility and pregnancy loss, whereas others sustain development – understanding these features of human genetic variation may provide insight into congenital disorders and their origins.”

Eva Hoffmann is Danish and was in 2015 recruited from UK to University of Copenhagen as Professor at ICMM.

Chuna Ram Choudhary

Chuna Ram Choudhary says: “The human body contains hundreds of different types of cells that perform different biological functions. Remarkably, all cells contain an identical copy of the genome, yet the same genetic information is differentially decoded in different cells, allowing activation of a different set of genes in different cells. Different gene products are then translated into different proteins that perform different functions, and ultimately give rise to functionally different cell types. Regulatory genome elements, called enhancers, act as central regulators of gene transcription and enable cell-type-specific differential decoding of the same genome. How enhancers control some genes, without affecting others, remains a major unresolved mystery in biology. This project aims to provide a deeper mechanistic understanding of gene expression regulation in mammalian cells and illuminate the molecular principles by which enhancers activate their target genes.”

Chuna Ram Choudhary is of Danish Nationality, born in India, has his PhD and postdoctoral experience from Germany, and was recruited as an associate professor to Center for Protein Research, University of Copenhagen in 2009, where he became Professor in 2013.

Elisabet Stener-Victorin

Polycystic ovary syndrome (PCOS) is the leading cause of female infertility and linked to type-2 diabetes and cancer. Progress in managing the disorder is hindered by lack of insight into the underlying mechanisms. We know that male hormones plays a key role and that PCOS runs in families. Recently we made the discovery that PCOS-like symptoms, induced by exposing pregnant mice to male hormone, are passed down from mothers to great-granddaughters. Moreover, we have indications that sons can transmit the disease as well.

I will take a multidisciplinary approach to get better insights into how PCOS is passed on in families. We will use human and mouse studies as well as state-of-the-art molecular techniques to dissect the key mechanisms that influence how the syndrome is passed on across generations both by women and men. My vision is to open new horizons for prevention strategies rather than managing symptoms, thereby markedly reducing the burden of the disease in both women and men.

Anu Suomalainen Wartiovaara

Diabetic retinopathy is the most common cause of blindness in working age people. The disease shows overgrowth of vasculature in the retina, which causes rupture of microvessels and edema in the tissue, with risk to retinal detachment and decreasing eyesight. Still, the underlying molecular mechanisms are poorly known, hampering development of treatments. We have found that a specific type of (DEL) cell in retina, previously considered to be “supportive”, has an important role in maintaining physiological balance in retina. If the mitochondria, the cellular “power plants”, are dysfunctional in these cells, the retinal vasculature shows overgrowth and develops disease signs mimicking diabetic retinopathy. This exciting project has high potential to find mechanistic targets amenable for interventions. We will explore the pathophysiology in deep molecular detail, using state-of-the-art tools and our long expertise in metabolism, to discover the molecular basis of neovascular retinopathy of diabetes type.

Rasmus Pagh

How do we ensure that we can trust systems that use data to make decisions? Lawmakers across the world are grappling with the question of how to properly regulate systems that collect, analyze, and use data. Getting the balance right is crucial. Too little regulation could increase the risk of compromising basic societal values and privacy. Too strict regulations will limit our possibilities for realizing the value and societal benefit of AI and big data analytics.

The Providentia project will advance algorithms for integrating and analyzing sensitive data – such as health data or medical records – in a secure way that preserves privacy and does not require all data to be transferred to a central location.

During the last decade, differential privacy has emerged as the gold standard for protecting private information, based on firm mathematical guarantees on how much private information can be deduced from data sets, analyses, or predictions that are released. Extending recent developments, the project will establish a research group focusing on differentially private algorithms in distributed settings. The goal is to enable data science when no entity holds all relevant data, and where privacy considerations make it impossible or undesirable to consolidate all data for central analysis. This is relevant, for instance, when using healthcare data to improve health outcomes via better prevention, diagnosis and treatment of disease.

The project name is inspired by the ancient Roman goddess Providentia who personifies the ability to foresee events and make suitable provision. In this spirit, the Providentia project seeks to provide the forethought needed to ensure that data scientists can make use of valuable sources of insight, also when data contains sensitive information.